Crowdsensing and Data: Intelligence for City Pulse

This book examines the transformative role of crowd-sourced data and AI-driven analytics in redefining urban environments. This book presents a thorough investigation into how large-scale and real-time data harnessed from mobile devices, sensors, and participatory inputs enhances urban systems, including transportation, public safety, sustainability, and civic engagement. Through cutting-edge data analytics, machine learning techniques, and scalable system architectures, the book demonstrates how intelligent urban management is achieved.

This book integrates theoretical foundations with applied perspectives, offering a structured discussion around three central domains including Urban Crowdsensing Practices (i. e. , concepts, models, and service patterns), Data Processing and Analytics (e. g. , data fusion, machine learning, and intelligent frameworks), and Technological Enablers (such as mobile sensing, IoT, and cloud-based systems). Key Contributions of this book are:

1. Innovative Integration of Technologies: Demonstrates the convergence of crowdsensing, AI, big data analytics, and IoT to support intelligent and responsive urban decision making.

2. Practical Applications and Case Studies: Showcases real-world implementations of crowdsensing, highlighting its tangible impact on smart city development and urban innovation.

3. Interdisciplinary and Forward-Looking Perspectives: Bridges academia, industry, and policy, offering actionable insights for researchers, engineers, planners, and decision-makers.

Chapter 1. Urban Intelligence in Motion: Crowdsensing as a Catalyst for Change. - Chapter 2. Paradigms and Practices of Urban Crowdsensing: A Comprehensive Exploration in Urban Informatics. - Chapter 3. Land Surface Temperature Patterns and Private Car Mobility: A Crowdsensing-Based Spatial Study in Tehran. - Chapter 4. Crowdsensing Security and Privacy Preservation for Trusted Smart Cities. - Chapter 5. Fusion of Vehicular Communications, Crowdsensing and Autonomous Agents to Acquire Urban Intelligence. - Chapter 6. Global Navigation Satellite System (GNSS) and Internet of Things (IoT) Assisted Smart Parking Concept for Urban Areas. - Chapter 7. Leveraging Augmented Reality and Reinforcement Learning for Optimizing Evacuation in Crowded Public Spaces. - Chapter 8. The Role of Crowdsensing Technologies in Urban Digital Twins. - Chapter 9. Urban Intelligence in Action: Shaping the Pulse of the Data-Driven City.